Epiflows: an R package for risk assessment of travel-related spread of disease.
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ABSTRACT:
SUBMITTER: Moraga P
PROVIDER: S-EPMC6738191 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundTravellers' risk perception is a key component of travel risk assessment because it influences the adequate implementation of safety precautions. The aims of this study are to validate a tool to analyse travellers' risk perception to identify which factors can influence it and how it changes upon return.MethodsThe Traveller's Risk Perception (TRiP) questionnaire was developed and administered to outpatients before and after travel in three travel clinics. A principal component analysis (PCA) was performed to validate the questionnaire and multivariate regression analysis was used to evaluate the effect of travellers' characteristics on the risk scores.ResultsA total of 1020 travellers completed the questionnaire. PCA identified two latent factors: 'generic-disseminated risks' and 'specific-circumstantial risks'. Cronbach's α was acceptable (0.76 and 0.70, respectively). The 'generic-disseminated risks' dimension scored higher than the 'specific-circumstantial risks' (p<0.001). The items with the highest scores were insect bites, gastrointestinal disorders and malaria. The mean scores were significantly lower after the travel for all items but one.ConclusionsThe TRiP questionnaire is a valid and reliable tool for rating travellers' perceptions. Staff in travel clinics should be trained to systematically assess travellers' risk perception in order to tailor the consultation according to specific information needs.
| S-EPMC7057134 | biostudies-literature
Project description:The recent pandemic caused by the 2019 outbreak of novel coronavirus (2019-nCoV or COVID-19) has affected more than 3.0 million people resulting ~?212,000 deaths across 215 countries/territories as on 28th April 2020. The importation of the cases owing to enormous international travels from the affected countries is the foremost reason for local cycle of transmission. For a country like India, the second most populous country in the world with ~?1.35 billion population, the management and control of 2019-nCoV domestic spread heavily relied on effective screening and strict quarantine of passengers arriving at various international airports in India from affected countries. Here, by extracting the data from FLIRT, an online airline database for more than 800 airlines, and scanning more than 180,000 flights and 39.9 million corresponding passenger seats during 4th - 25th March, we show that India experienced the highest risk index of importing the passengers from middle eastern airports. Contrary to perception, travelers from China imposed lowest risk of importing the infected cases in India. This is clearly evident form the fact that while the number of infected cases were on the peak in China India was one of the least affected countries. The number of cases in India started exhibiting a sharp increase in the infected cases only after the European countries and USA recorded large number of infected cases. We further argue that while the number of cases in middle eastern countries may still be very low, the airports in middle eastern countries, particularly Dubai, being one of the largest transit hubs for international passengers, including arriving in India, might have posed a higher risk of getting infected with 2019-nCoV. We suggest that any future travel related disease infection screening at the airports should critically assess the passengers from major transit hubs in addition to affected country of origin.
| S-EPMC7216130 | biostudies-literature
Project description:BackgroundMuch research in epidemiology has been focused on evaluating conventional methods of control strategies in the event of an epidemic or pandemic. Travel restrictions are often suggested as an efficient way to reduce the spread of a contagious disease that threatens public health, but few papers have studied in depth the effects of travel restrictions. In this study, we investigated what effect different levels of travel restrictions might have on the speed and geographical spread of an outbreak of a disease similar to severe acute respiratory syndrome (SARS).MethodsWe used a stochastic simulation model incorporating survey data of travel patterns between municipalities in Sweden collected over 3 years. We tested scenarios of travel restrictions in which travel over distances >50 km and 20 km would be banned, taking into account different levels of compliance.ResultsWe found that a ban on journeys >50 km would drastically reduce the speed and geographical spread of outbreaks, even when compliance is < 100%. The result was found to be robust for different rates of intermunicipality transmission intensities.ConclusionThis study supports travel restrictions as an effective way to mitigate the effect of a future disease outbreak.
| S-EPMC1764026 | biostudies-literature
Project description:Long-distance dispersal pathways, which frequently relate to human activities, facilitate the spread of alien species. One pathway of concern in North America is the possible spread of forest pests in firewood carried by visitors to campgrounds or recreational facilities. We present a network model depicting the movement of campers and, by extension, potentially infested firewood. We constructed the model from US National Recreation Reservation Service data documenting more than seven million visitor reservations (including visitors from Canada) at campgrounds nationwide. This bi-directional model can be used to identify likely origin and destination locations for a camper-transported pest. To support broad-scale decision making, we used the model to generate summary maps for 48 US states and seven Canadian provinces that depict the most likely origins of campers traveling from outside the target state or province. The maps generally showed one of two basic spatial patterns of out-of-state (or out-of-province) origin risk. In the eastern United States, the riskiest out-of-state origin locations were usually found in a localized region restricted to portions of adjacent states. In the western United States, the riskiest out-of-state origin locations were typically associated with major urban areas located far from the state of interest. A few states and the Canadian provinces showed characteristics of both patterns. These model outputs can guide deployment of resources for surveillance, firewood inspections, or other activities. Significantly, the contrasting map patterns indicate that no single response strategy is appropriate for all states and provinces. If most out-of-state campers are traveling from distant areas, it may be effective to deploy resources at key points along major roads (e.g., interstate highways), since these locations could effectively represent bottlenecks of camper movement. If most campers are from nearby areas, they may have many feasible travel routes, so a more widely distributed deployment may be necessary.
| S-EPMC4090238 | biostudies-literature
Project description:Gut microbiota and Antimicrobial resistance alteration during international travel in Hong Kong traveler
| PRJEB36968 | ENA
Project description:Human travel is one of the primary drivers of infectious disease spread. Models of travel are often used that assume the amount of travel to a specific destination decreases as cost of travel increases with higher travel volumes to more populated destinations. Trip duration, the length of time spent in a destination, can also impact travel patterns. We investigated the spatial patterns of travel conditioned on trip duration and find distinct differences between short and long duration trips. In short-trip duration travel networks, trips are skewed towards urban destinations, compared with long-trip duration networks where travel is more evenly spread among locations. Using gravity models to inform connectivity patterns in simulations of disease transmission, we show that pathogens with shorter generation times exhibit initial patterns of spatial propagation that are more predictable among urban locations. Further, pathogens with a longer generation time have more diffusive patterns of spatial spread reflecting more unpredictable disease dynamics.
| S-EPMC8378725 | biostudies-literature
Project description:Due to the suspension of in-person classes in response to the COVID-19 pandemic, students at universities with earlier spring breaks traveled and returned to campus while those with later spring breaks largely did not. We use variation in academic calendars to study how travel affected the evolution of COVID-19 cases and mortality. Estimates imply that counties with more early spring break students had a higher growth rate of cases than counties with fewer early spring break students. The increase in case growth rates peaked two weeks after spring break. Effects are larger for universities with students more likely to travel through airports, to New York City, and to popular Florida destinations. Consistent with secondary spread to more vulnerable populations, we find a delayed increase in mortality growth rates. Lastly, we present evidence that viral infection transmission due to college student travel also occurred prior to the COVID-19 pandemic.
| S-EPMC7962882 | biostudies-literature
Project description:This study examines the effects of season and weather on mood (valence and activation) and travel satisfaction (measured by the Satisfaction with Travel Scale). Analyses are presented of 562 time-sampled morning commutes to work made by 363 randomly sampled people in three different Swedish cities asking them to use smartphones to report their mood in their home before and directly after the commutes. These reports as well as satisfaction with the commute obtained in summer and winter are linked to weather data and analyzed by means of fixed-effects regression analyses. The results reveal main effects of weather (temperature and precipitation) on mood and travel satisfaction (temperature, sunshine, precipitation, and wind speed). The effects of weather on mood and travel satisfaction differ depending on travel mode. Temperature leads to a more positive mood, wind leads to higher activation for public transport users, and sunshine leads to a more negative mood for cyclists and pedestrians. Sunshine and higher temperatures make travel more relaxed although not for cycling and walking, and rain and snow lead to a higher cognitive assessed quality of travel.
| S-EPMC5292578 | biostudies-literature
Project description:Air travel has a decisive role in the spread of infectious diseases at the global level. We present a methodology applied during the early stages of the COVID-19 pandemic that uses detailed aviation data at the final destination level in order to measure the risk of the disease spreading outside China. The approach proved to be successful in terms of identifying countries with a high risk of infected travellers and as a tool to monitor the evolution of the pandemic in different countries. The high number of undetected or asymptomatic cases of COVID-19, however, limits the capacity of the approach to model the full dynamics. As a result, the risk for countries with a low number of passengers from Hubei province appeared as low. Globalization and international aviation connectivity allow travel times that are much shorter than the incubation period of infectious diseases, a fact that raises the question of how to react in a potential new pandemic.
| S-EPMC7277792 | biostudies-literature
Project description:BackgroundA novel coronavirus (2019-nCoV) emerged in Wuhan City, China, at the end of 2019 and has caused an outbreak of human-to-human transmission with a Public Health Emergency of International Concern declared by the World Health Organization on January 30, 2020.AimWe aimed to estimate the potential risk and geographic range of Wuhan novel coronavirus (2019-nCoV) spread within and beyond China from January through to April, 2020.MethodsA series of domestic and international travel network-based connectivity and risk analyses were performed, by using de-identified and aggregated mobile phone data, air passenger itinerary data, and case reports.ResultsThe cordon sanitaire of Wuhan is likely to have occurred during the latter stages of peak population numbers leaving the city before Lunar New Year (LNY), with travellers departing into neighbouring cities and other megacities in China. We estimated that 59,912 air passengers, of which 834 (95% UI: 478 - 1349) had 2019-nCoV infection, travelled from Wuhan to 382 cities outside of mainland China during the two weeks prior to the lockdown of Wuhan. The majority of these cities were in Asia, but major hubs in Europe, the US and Australia were also prominent, with strong correlation seen between predicted importation risks and reported cases. Because significant spread has already occurred, a large number of airline travellers (3.3 million under the scenario of 75% travel reduction from normal volumes) may be required to be screened at origin high-risk cities in China and destinations across the globe for the following three months of February to April, 2020 to effectively limit spread beyond its current extent.ConclusionFurther spread of 2019-nCoV within China and international exportation is likely to occur. All countries, especially vulnerable regions, should be prepared for efforts to contain the 2019-nCoV infection.
| S-EPMC7276059 | biostudies-literature